Version 1
: Received: 13 March 2020 / Approved: 15 March 2020 / Online: 15 March 2020 (12:38:03 CET)
How to cite:
Henchiri, M.; Liu, Q.; Essifi, B.; Ali, S.; Kalisa, W.; Zhang, S.; Yun, B.; Zhang, J. Identification of Drought and Performance Evaluation of MODIS and TRMM through Remote Sensing: A Case Study in North and West Africa during 2002–2018. Preprints2020, 2020030241. https://doi.org/10.20944/preprints202003.0241.v1
Henchiri, M.; Liu, Q.; Essifi, B.; Ali, S.; Kalisa, W.; Zhang, S.; Yun, B.; Zhang, J. Identification of Drought and Performance Evaluation of MODIS and TRMM through Remote Sensing: A Case Study in North and West Africa during 2002–2018. Preprints 2020, 2020030241. https://doi.org/10.20944/preprints202003.0241.v1
Henchiri, M.; Liu, Q.; Essifi, B.; Ali, S.; Kalisa, W.; Zhang, S.; Yun, B.; Zhang, J. Identification of Drought and Performance Evaluation of MODIS and TRMM through Remote Sensing: A Case Study in North and West Africa during 2002–2018. Preprints2020, 2020030241. https://doi.org/10.20944/preprints202003.0241.v1
APA Style
Henchiri, M., Liu, Q., Essifi, B., Ali, S., Kalisa, W., Zhang, S., Yun, B., & Zhang, J. (2020). Identification of Drought and Performance Evaluation of MODIS and TRMM through Remote Sensing: A Case Study in North and West Africa during 2002–2018. Preprints. https://doi.org/10.20944/preprints202003.0241.v1
Chicago/Turabian Style
Henchiri, M., Bai Yun and Jiahua Zhang. 2020 "Identification of Drought and Performance Evaluation of MODIS and TRMM through Remote Sensing: A Case Study in North and West Africa during 2002–2018" Preprints. https://doi.org/10.20944/preprints202003.0241.v1
Abstract
North and West Africa are the most vulnerable regions to drought, due to the high variation in monthly precipitation. An accurate and efficient monitoring of drought is essential. In this study, we use TRMM data with remote sensing tools for effective monitoring of drought. The Drought Severity Index (DSI), Temperature Vegetation Drought Index (TVDI), Normalized Difference Vegetation Index (NDVI), and Normalized Vegetation Supply Water Index (NVSWI) are more useful for monitoring the drought over North and West Africa. To classify the areas affected by drought, we used the TRMM spatial maps to verify the TVDI, DSI and NVSWI indexes derived from MODIS. The DSI, TVDI, NVSWI and Monthly Precipitation Anomaly (NPA) indexes with the employ of MODIS-derived ET/PET and NDVI were chosen for monitoring the drought in the study area. The seasonal spatial correlation between the DSI, NPA, NVWSI, NDVI, TVDI and TCI indicates that NVSWI, NDVI and DSI present an excellent monitor of drought indexes. The change trend of drought from 2002 to 2018 was also characterized. The frequency of drought showed a decrease during this period.
Keywords
North and West Africa; drought; DSI; TVDI; NVSWI; spatial correlation; change trend of drought
Subject
Environmental and Earth Sciences, Remote Sensing
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
